Context hygiene layer for AI coding agents that prunes failed-attempt traces

Long agent sessions degrade because every abandoned code attempt and stack trace stays in the conversation history and crowds out what matters. A pruning/summarization layer in front of the model call could keep agents productive and cut token spend.

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